Influence of convective parameterization on the systematic errors of Climate Forecast System (CFS) model over the Indian monsoon region from an extended range forecast perspective |
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| Authors: | S Pattnaik S Abhilash S De A K Sahai R Phani B N Goswami |
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| Institution: | 1. School of Earth, Ocean and Climate Sciences, Indian Institute of Technology Bhubaneswar, Bhubaneswar, India
2. Indian Institute of Tropical Meteorology (I.I.T.M), Pune, India
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| Abstract: | This study investigates the influence of Simplified Arakawa Schubert (SAS) and Relax Arakawa Schubert (RAS) cumulus parameterization schemes on coupled Climate Forecast System version.1 (CFS-1, T62L64) retrospective forecasts over Indian monsoon region from an extended range forecast perspective. The forecast data sets comprise 45 days of model integrations based on 31 different initial conditions at pentad intervals starting from 1 May to 28 September for the years 2001 to 2007. It is found that mean climatological features of Indian summer monsoon months (JJAS) are reasonably simulated by both the versions (i.e. SAS and RAS) of the model; however strong cross equatorial flow and excess stratiform rainfall are noted in RAS compared to SAS. Both the versions of the model overestimated apparent heat source and moisture sink compared to NCEP/NCAR reanalysis. The prognosis evaluation of daily forecast climatology reveals robust systematic warming (moistening) in RAS and cooling (drying) biases in SAS particularly at the middle and upper troposphere of the model respectively. Using error energy/variance and root mean square error methodology it is also established that major contribution to the model total error is coming from the systematic component of the model error. It is also found that the forecast error growth of temperature in RAS is less than that of SAS; however, the scenario is reversed for moisture errors, although the difference of moisture errors between these two forecasts is not very large compared to that of temperature errors. Broadly, it is found that both the versions of the model are underestimating (overestimating) the rainfall area and amount over the Indian land region (and neighborhood oceanic region). The rainfall forecast results at pentad interval exhibited that, SAS and RAS have good prediction skills over the Indian monsoon core zone and Arabian Sea. There is less excess rainfall particularly over oceanic region in RAS up to 30 days of forecast duration compared to SAS. It is also evident that systematic errors in the coverage area of excess rainfall over the eastern foothills of the Himalayas remains unchanged irrespective of cumulus parameterization and initial conditions. It is revealed that due to stronger moisture transport in RAS there is a robust amplification of moist static energy facilitating intense convective instability within the model and boosting the moisture supply from surface to the upper levels through convergence. Concurrently, moisture detrainment from cloud to environment at multiple levels from the spectrum of clouds in the RAS, leads to a large accumulation of moisture in the middle and upper troposphere of the model. This abundant moisture leads to large scale condensational heating through a simple cloud microphysics scheme. This intense upper level heating contributes to the warm bias and considerably increases in stratiform rainfall in RAS compared to SAS. In a nutshell, concerted and sustained support of moisture supply from the bottom as well as from the top in RAS is the crucial factor for having a warm temperature bias in RAS. |
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